Discernment for user experience
Discernment for user experience · 2 min
As AI speeds up implementation, design becomes the differentiator. This lesson covers the UX principles that matter most when working with AI, why “make it look good” produces nothing useful, and how to close the gap between a critique you’d give a colleague and a description AI can execute.
Key takeaways
- When implementation is fast, experience is the differentiator. Design literacy is a core builder skill.
- “Make it look good” is a wish, not a spec. Describe experience with the same precision as a function.
- AI does not get accessibility right by default. Specify it, then audit what you get back.
- A good critique and an actionable AI description are different artifacts. Learn to translate between them.
Exercise
The Clinic Wait Time Project, Part 3
Write a design spec for your clinic app — user flows, information hierarchy, interaction patterns — then rebuild it with AI against that spec. Critique the result: where did AI nail it, and where is it technically correct but experientially flat? Run a quick accessibility audit and document what AI missed.
- Clarity & Mental Model — Does the output use language and patterns a clinic admin would recognize?
- Information Hierarchy — Is the most important information the first thing users see?
- Accessibility — Does it pass color contrast, screen reader, and keyboard navigation checks?
- Feedback & Error Handling — Does the interface acknowledge user actions and explain what to do when something goes wrong?
Lesson reflection
- How much of your design spec describes what the interface does versus how it should feel to use?
- After running the accessibility check, did you build with accessibility in mind from the start, or add it at the end?
What's next
You’ve looked at your Clinic Wait Time Checker through both a code lens and a UX lens. In the next lesson, you’ll tackle the hardest question: what does it mean to actually stand behind what you build?